Gene expression data from isolated white winter wheat embryos at physiological maturity, environment 2 of 2.
Ontology highlight
ABSTRACT:
ORGANISM(S): Triticum aestivum
SUBMITTER: Jesse Munkvold
PROVIDER: E-GEOD-35407 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Gene expression was measured in isolated wheat embryos at physiological maturity. The gene expression measurements were done across a doubled haploid white winter wheat population between the variety Cayuga and the variety Caledonia (CxC). Data can be used for mapping gene expression QTL (eQTL). These data are from the first (Helfer 2004) of two field environments. Different target labeling was used so the environments are contained in two separate series. The design was a two-channel dye-swap reference design with bulked total RNA from pre-anthesis wheat spikes serving as the reference. Normalization was done using the TIGR MIDAS suite using blockwise LOWESS smoothing and variance normalization. Between slide variance normalization was also done for all slides so direct comparisons could be made. Dye-swap was submitted unmerged to facilitate flexibility in downstream processing.
2012-02-01 | E-GEOD-35300 | biostudies-arrayexpress
Project description:Gene expression was measured in isolated wheat embryos at physiological maturity. The gene expression measurements were done across a doubled haploid white winter wheat population between the variety Cayuga and the variety Caledonia (CxC). Data can be used for mapping gene expression QTL (eQTL). These data are from the second (Ketola 2005) of two field environments. Different target labeling was used so the environments are contained in two separate series.
2012-02-01 | GSE35407 | GEO
Project description:Gene expression was measured in isolated wheat embryos at physiological maturity. The gene expression measurements were done across a doubled haploid white winter wheat population between the variety Cayuga and the variety Caledonia (CxC). Data can be used for mapping gene expression QTL (eQTL). These data are from the first (Helfer 2004) of two field environments. Different target labeling was used so the environments are contained in two separate series.
2012-02-01 | GSE35300 | GEO
Project description:Using 270K Nimblegen Comparative Genomic Hybridization (CGH) array on a set of cv. Chinese Spring deletion lines, a total of 3,671 sequence contigs and scaffolds (~7.8% of chromosome 7B physical length) were mapped into nine deletion bins. In our study we have developed 270K CGH Nimblegen array containing wheat 7B chromosome specific probes and genotyped wheat 7B deletion stocks which have terminal deletions in 7B. Our main aim was to identify absent probes (sequences) in deletion lines. Initially, spatial normalization and M-A loess normalization was performed for comparison test/reference and then clustering analysis (Mcust) was carried out. Further analysis was done on scaffolds (i.e. on larger sequences instead of probes; probes are designed from scaffolds)
2014-05-09 | GSE57461 | GEO
Project description:Wheat (Triticum aestivum ssp. aestivum) contributes to 20% of the human protein supply, delivers essential amino acids and is of fundamental importance for bread and pasta quality. Wheat proteins are also involved in adverse human reactions like celiac disease, wheat allergy and the non-celiac wheat sensitivity (NCWS). Using LC-MS-based LFQ proteomics of aqueous flour extracts we determined 756 proteins across 150 wheat varieties grown in three environments. However, only 303 proteins were stably expressed across all environments in at least one variety underlining the large influence of environmental conditions on the expression of many proteins. Moreover, only 89 proteins were comparably expressed by all 150 varieties, with high coefficients of variation for the other proteins. Heritability (h) ranged from 0-1 with 114 proteins having h² > 0.6. Therefore, the expression of the variable proteins should be amenable to targeted manipulation across the wheat supply chain by varietal choice and breeding. Our study provides a first approach towards a fast and high-throughput methodology for quantifying these proteins which is required to breed wheats with the desired properties. Amylase trypsin inhibitors (ATIs) appear as a potential trigger for NCWS inducing intestinal and extra-intestinal inflammation. Studies on the prevalence and genetic architecture of ATI proteins in wheat are lacking so far. Large differences in the content and composition of 8 ATIs in the different varieties were identified by QconCAT-assisted quantification. The ATI proteins had low coefficients of correlations with quality traits commonly analyzed in wheat breeding. However, heritability was quite low except for ATI 0.28 and ATI CM2. A genome wide association mapping revealed a complex genetic architecture built up on many small but few medium and two major quantitative trait loci (QTL). The latter were on chromosome 3B for ATI 0.19-like and 6B for ATI 0.28 explaining 70.6 and 68.7% of the genetic variance, respectively. Using the wheat reference genome sequence, seven potential candidate genes behind the medium and major QTL were described with only one showing polymorphism based on exome capture analysis. Consequently, wheat breeding could contribute to a reduction of ATI contents in wheat products if incidence of ATI on human health is further confirmed.
2021-09-10 | PXD023654 | Pride
Project description:Using 270K Nimblegen Comparative Genomic Hybridization (CGH) array on a set of cv. Chinese Spring deletion lines, a total of 3,671 sequence contigs and scaffolds (~7.8% of chromosome 7B physical length) were mapped into nine deletion bins. In our study we have developed 270K CGH Nimblegen array containing wheat 7B chromosome specific probes and genotyped wheat 7B deletion stocks which have terminal deletions in 7B. Our main aim was to identify absent probes (sequences) in deletion lines. Initially, spatial normalization and M-A loess normalization was performed for comparison test/reference and then clustering analysis (Mcust) was carried out. Further analysis was done on scaffolds (i.e. on larger sequences instead of probes; probes are designed from scaffolds) Hybridization of DNA from 13 wheat lines, including 11 Chinese Spring cytogenetic stocks (Del7BL-9, DT7BL, DT7BS, Del7BL-13, Del7BL-14, Del7BL-5, Del7BL-1, Del7BL-7Del1DS-3, Del7BL-2,Del7BS-2, Del7BL-3) and 2 replicates of Langdon (LDN) tetraploid wheat. A set of 49,500 7B chromosome specific features (ISBP probes and random genomic features) and 18,000 control probes with each probe replicated four times on the 270K chip.
2014-05-09 | E-GEOD-57461 | biostudies-arrayexpress
Project description:Microarray data analysis Intensity of 21,939 gene features per array was extracted from scanned microarray images using Feature Extraction 5.1.1 software (Agilent Technologies), which performs background subtractions and dye normalization. This normalization method is targeted at detecting changes in relative expression of individual genes rather than global expression. Global expression change would require external normalization controls (van de Peppel et al., 2003). Text output was processed using an application developed in-house to perform ANOVA analysis (http://lgsun.grc.nia.nih.gov/ANOVA/). Intensity of features measured with a >50% error were replaced with missing values except features with very low intensity. Surrogate values equal to mean error were inserted for values that were negative or less than the probe error. Data were analyzed using ANOVA with embryonic stage as a factor. The small number of biological replications typical in expression profiling experiments results in a highly variable error variance, and this problem is usually addressed by log-ratio thresholds (Schena et al., 1995) that require subjective decisions about biological significance, or by Bayesian adjustment of error variance (Baldi and Long, 2001), which may still underestimate error variance and result in false positive results. To reduce false-positives, we opted for a very conservative error model in which error variance that is used for estimating F-statistics is the maximum of the actual error variance for this gene and the average error variance in 500 genes with similar average intensity. Statistical significance was determined using the False Discovery Rate (FDR = 10%) method (Benjamini and Hochberg, 1995). Pair-wise mean comparison was done with t-statistics and FDR=10%. Further data processing including scatter plots, hierarchical clustering, and principal component analysis (PCA) were also performed through NIA microarray analysis tool (http://lgsun.grc.nia.nih.gov/ANOVA/). The input file for NIA microarray analysis tool is available at http://lgsun.grc.nia.nih.gov/microarray/data.html
2004-01-30 | E-MEXP-73 | biostudies-arrayexpress
Project description:Feature Extraction 5.1.1 software (Agilent Technologies) performs background subtractions and dye normalization. This normalization method is targeted at detecting changes in relative expression of individual genes rather than global expression. Global expression change would require external normalization controls (van de Peppel et al., 2003). Text output was processed using an application developed in-house to perform ANOVA analysis (http://lgsun.grc.nia.nih.gov/ANOVA/). Intensity of features measured with a >50% error were replaced with missing values except features with very low intensity. Surrogate values equal to mean error were inserted for values that were negative or less than the probe error. Data were analyzed using ANOVA with embryonic stage as a factor. The small number of biological replications typical in expression profiling experiments results in a highly variable error variance, and this problem is usually addressed by log-ratio thresholds (Schena et al., 1995) that require subjective decisions about biological significance, or by Bayesian adjustment of error variance (Baldi and Long, 2001), which may still underestimate error variance and result in false positive results. To reduce false-positives, we opted for a very conservative error model in which error variance that is used for estimating F-statistics is the maximum of the actual error variance for this gene and the average error variance in 500 genes with similar average intensity. Statistical significance was determined using the False Discovery Rate (FDR = 10%) method (Benjamini and Hochberg, 1995). Pair-wise mean comparison was done with t-statistics and FDR=10%. Further data processing including scatter plots, hierarchical clustering, and principal component analysis (PCA) were also performed through NIA microarray analysis tool (http://lgsun.grc.nia.nih.gov/ANOVA/). Details are described in the publication (Hamatani T. et al., Developmental Cell. Published online Dec. 18, 2003).
2004-01-12 | E-MEXP-74 | biostudies-arrayexpress
Project description:Centromeres typically contain repeat sequences, but centromere function does not necessarily depend on these sequences. In aneuploid wheat (Triticum aestivum) and wheat distant hybridization offspring, we found functional centromeres with dramatic changes to centromeric retrotransposon of wheat (CRW) sequences. CRW sequences were greatly reduced in the ditelosomic lines 1BS, 5DS, 5DL, and a wheat-Thinopyrum elongatum addition line. CRWs were completely lost in the ditelosomic line 4DS, but a 994 kb ectopic genomic DNA sequence was involved in de novo centromere formation on the 4DS chromosome. In addition, two ectopic sequences were incorporated in a de novo centromere in a wheat-Th. intermedium addition line. Centromeric sequences were also expanded to the chromosome arm in wide hybridizations. Stable alien chromosomes with two and three regions containing centromeric sequences were found in wheat-Th. elongatum hybrid derivatives, but only one is functional. In wheat-rye (Secale cereale) hybrids, rye centromere specific sequences spread to the chromosome arm and may cause centromere expansion. Thus, distant wheat hybridizations cause frequent and significant changes to the centromere via centromere misdivision, which may affect retention or loss of alien chromosomes in hybrids. ChIP-seq was carried out with anti-CENH3 antibody using material 4DS and control (Chinese Spring, CS as short).
2016-04-02 | E-GEOD-63752 | biostudies-arrayexpress
Project description:Introduction: Pre-harvest Sprouting (PHS) seriously affects wheat quality and yield. However, to date there have been limited reports. It is of great urgency to breed resistance varieties via quantitative trait nucleotides (QTNs) or genes for PHS resistance in white-grained wheat. Methods: 629 Chinese wheat varieties, including 373 local wheat varieties from 70 years ago and 256 improved wheat varieties were phenotyped for spike sprouting (SS) in two environments and genotyped by wheat 660K microarray. These phenotypes were used to associate with 314,548 SNP markers for identifying QTNs for PHS resistance using several multi-locus genome-wide association study (GWAS) methods. Their candidate genes were verified by RNA-seq, and the validated candidate genes were further exploited in wheat breeding. Results: As a result, variation coefficients of 50% and 47% for PHS in 629 wheat varieties, respectively, in 2020-2021 and 2021-2022 indicated large phenotypic variation, in particular, 38 white grain varieties appeared at least medium resistance, such as Baipimai, Fengchan 3, and Jimai 20. In GWAS, 22 significant QTNs, with the sizes of 0.06% ~ 38.11%, for PHS resistance were stably identified by multiple multi-locus methods in two environments, e.g., AX-95124645 (chr3D:571.35Mb), with the sizes of 36.390% and 45.850% in 2020-2021 and 2021-2022, respectively, was detected by several multi-locus methods in two environments. As compared with previous studies, the AX-95124645 was used to develop Kompetitive Allele-Specific PCR marker QSS.TAF9-3D (chr3D:569.17Mb~573.55Mb) for the first time, especially, it is available in white-grain wheat varieties. Around this locus, nine genes were significantly differentially expressed, and two of them (TraesCS3D01G466100 and TraesCS3D01G468500) were found by GO annotation to be related to PHS resistance and determined as candidate genes. Discussion: The QTN and two new candidate genes related to PHS resistance were identified in this study. The QTN can be used to effectively identify the PHS resistance materials, especially, all the white-grained varieties with QSS.TAF9-3D-TT haplotype are resistant to spike sprouting. Thus, this study provides candidate genes, materials, and methodological basis for breeding wheat PHS resistance in the future.
2023-01-08 | GSE222342 | GEO